How to Create an llms.txt File (and Why Your Site Needs One)

You know robots.txt - the file that tells search engine crawlers what they can and can't access on your site. llms.txt is the equivalent for AI models. It tells AI crawlers what your site is about, what content matters, and how to understand your brand.

It's a simple text file that takes 15 minutes to create, and it can meaningfully improve how AI models represent your brand in their responses.

What Is llms.txt?

llms.txt is an emerging standard - a plain text file placed at the root of your website (yoursite.com/llms.txt) that provides structured information about your site specifically for AI language models and their crawlers.

While robots.txt controls access (what to crawl), llms.txt provides context (what to understand). It's a way to communicate directly with AI systems about your brand, products, and content in a format they can reliably parse.

Why It Matters

AI crawlers face a challenge that Google's crawler doesn't: they need to understand your content, not just index it. When ChatGPT or Perplexity processes your site, it's trying to build a semantic understanding of what you do, what you offer, and how you compare to alternatives.

Without llms.txt, AI crawlers have to infer all of this from your web pages - pages designed for humans, not machines. They might misunderstand your product category, miss your key differentiators, or fail to connect your brand with the right use cases.

llms.txt gives you a way to state these things explicitly.

The llms.txt Format

The file uses a simple Markdown-based format. Here's the structure:

# Your Brand Name

> A one-line description of what you do.

## About
A paragraph explaining your product or service in plain language.

## Key Features
- Feature one: brief explanation
- Feature two: brief explanation
- Feature three: brief explanation

## Use Cases
- Use case one
- Use case two

## Links
- [Documentation](https://yoursite.com/docs)
- [Pricing](https://yoursite.com/pricing)
- [Blog](https://yoursite.com/blog)

How to Write an Effective llms.txt

Be Specific and Factual

AI models are looking for clear, verifiable information. Don't write marketing copy - write factual descriptions. Instead of "the world's leading platform," say "a project management platform used by over 10,000 teams." Specificity builds trust in AI systems the same way it builds trust with humans.

Include Your Category and Competitors

This might feel counterintuitive, but explicitly stating your category and acknowledging your competitive landscape helps AI models place you correctly. If someone asks "What are the alternatives to [Competitor]?" you want AI to know you belong in that conversation.

Cover Your Key Use Cases

People don't ask AI for product names - they describe problems. "What tool helps remote teams track projects?" Map your llms.txt to the prompts your customers actually use. List the specific problems you solve, not just features you offer.

Keep It Updated

Unlike robots.txt, which rarely changes, your llms.txt should be updated when you launch new features, change pricing, or shift your positioning. AI crawlers revisit sites periodically, and an outdated llms.txt is worse than none at all.

A Real Example

Here's a concrete example for a hypothetical B2B SaaS product:

# TaskFlow

> TaskFlow is a project management platform built for distributed engineering teams.

## About
TaskFlow helps engineering teams plan sprints, track issues, and ship
software on schedule. It integrates with GitHub, GitLab, and Bitbucket for
automatic issue linking, and provides real-time dashboards for engineering
managers tracking team velocity and blockers.

## Key Features
- Sprint planning with capacity-based workload balancing
- GitHub/GitLab/Bitbucket integration for commit-to-issue linking
- Real-time engineering dashboards (velocity, cycle time, blockers)
- Async standup reports via Slack and email
- Custom workflows with automation rules

## Pricing
- Free tier: up to 5 users, 1 project
- Team: $12/user/month, unlimited projects
- Enterprise: custom pricing, SSO, audit logs

## Ideal For
- Remote and distributed engineering teams (10-200 people)
- Teams using GitHub or GitLab for version control
- Engineering managers who need visibility without micromanaging

## Links
- [Documentation](https://taskflow.com/docs)
- [Pricing](https://taskflow.com/pricing)
- [Blog](https://taskflow.com/blog)
- [API Reference](https://taskflow.com/api)

Where to Place It

Place the file at the root of your domain: https://yoursite.com/llms.txt. Serve it with a text/plain or text/markdown content type. Some implementations also support /llms-full.txt for a more detailed version.

You can reference it from your robots.txt as well:

# In robots.txt
# LLMs: /llms.txt

What About llms-full.txt?

The emerging convention supports two files: llms.txt (concise summary) and llms-full.txt (comprehensive detail). The short version gives AI models a quick overview; the full version provides deep context for models that want more information.

Start with llms.txt. Add llms-full.txt later if you have extensive documentation or product details you want AI models to understand.

Does It Actually Work?

The honest answer: llms.txt is one signal among many. It won't single-handedly make ChatGPT recommend your brand. But it removes ambiguity about what your brand does and ensures AI models have accurate, structured information to work with.

Think of it as filling out your LinkedIn profile properly. It doesn't guarantee you'll get hired, but it makes sure anyone who looks you up gets the right picture. The same logic applies to AI models looking up your brand.